Field of the Invention
The present invention relates to a method of indicating the probability of non-epileptic seizures, such as psychogenic non-epileptic seizures (PNES), wherein the method comprises the steps:                automatically recording data on a patient by means of a first device placed on the body of the patient, wherein at least one sensor unit in the device measures at least one parameter on the body of the patient, and wherein the data is recorded over a predetermined time period;        transmitting the data from the first device to a computer unit for further analysis; and        manually logging data comprising at least a first time stamp of at least one seizure within that time period.        
The present invention further relates to a system for indicating the probability of non-epileptic seizures, such as psychogenic non-epileptic seizures, comprising:                a first device configured to be placed on the body of a patient, wherein the first device comprises at least one sensor unit configured to measure at least one parameter on the body of the patient, wherein the first device is configured to automatically record data over a predetermined time period;        a computer unit configured to be coupled to the first device and comprising data processing means configured to analyze the recorded data; and        means for manually logging data comprising at least a first time stamp of at least one seizure within that time period.        
Description of Related Art
Today, seizures are a symptom for several diseases, which may make it hard for the doctors to diagnose the cause, especially due to the seizures resemblance with epileptic seizures. In particular psychogenic non-epileptic seizures (called PNES or NEAD) look very similar to epileptic seizures. This means that patients are often misdiagnosed, and resent studies have indicated that up to one-fourth of patients have been misdiagnosed. Correcting the diagnosis often involves a time-consuming and costly process. Especially, PNES similar to generalized tonic-clonic epileptic seizures (called GTCS) are hard to distinguish from actual GTCS without video and EEG (electroencephalography) recordings of the seizures.
Therefore, people suffering from PNES are often admitted to special clinics or hospitals where the medical staffs, such as physician, primary caregivers, doctors or neurologists, are able to monitor and record such seizures in order to determine the type of seizure and prepare a treatment. Once admitted, the patient is often coupled to an epilepsy monitoring unit (called an EMU) where seizures may be recorded on video combined with EEG-measurements. Such admissions in an EMU are very expensive and may cost as much as DKK 60,000 (about US$ 8,750), and requires the patient to be admitted for several hours or days in order to record a suitable amount of seizures. Provocative tests may be used by the staff to trigger seizures, if the seizures do not occur naturally during admission.
Today, video-EEG monitoring (called video-EEG) is the gold standard for detecting epilepsy and PNES. Both modalities are needed, and video monitoring alone does not provide an accurate way of detecting seizures. The EEG measurement involves the use a plurality of electrodes attached to the brain of the patient which are then coupled to a data logger or a data processing unit. Today, small portable EEG-devices may be coupled to the electrodes so that the patient is able to move around, but the multiple electrodes still provides some discomfort for the patient and increases the risk that one or more of the electrodes accidently fall off or are pulled off. Video-EEG is also used for verifying the accuracy (false detection rate) of seizure detection systems, however they still require the patient to be admitted and coupled to an EEG system.
The article “Can Cortical Silent period and Motor Threshold be Practical Parameters in the Comparison of Patients with Generalized Epilepsy and Patients with Psychogenic Non-Epileptic Seizures?”, Ipekdal et al., Eur Neurol, 2013, discloses a method of distinguishing between a GTCS and a PNES where the patients were coupled to an EEG-device with a plurality of electrodes. The patients were admitted to a hospital and magnetically stimulated in the area controlling the ABP muscles of the brain by TMS. EMG electrodes placed on the ABP muscles are used to regulate the applied stimulate. The article teaches that cortical silent periods in the recorded EEG-signals are prolonged for patients with GTCS compared to patients with PNES. The article does not teach or suggest that the amplitude of the muscle activity may be used to detect PNES, since they found no significant differences in the recorded motor thresholds. This method requires patients to be admitted for at least two days which presents a time-consuming and costly process. The patients have to be subjected to a stimulant in the TSM test which may lead to some discomfort for the patient, as mentioned in the article.
The article “Use of postictal respiratory pattern to discriminate between convulsive psychogenic nonepileptic seizures and generalized tonic-clonic seizures”, Rosemergy et al., Epilepsy Behav., April 2013, discloses a method of distinguishing between a GTCS and a PNES where the patients were admitted to a hospital and coupled to a video-monitoring unit. The postictal phase was then recorded at each seizure. This article teaches that the postictal respiratory response (rate and pattern) is significantly longer for patients with GTCS compared to patients with PNES. As mentioned in the article, the patient needs to be placed relative to the camera so that the respiratory response can be recorded, which is not always possible. The patient still needs to be admitted in order to get a proper video-recording of the patient.
The article “Detection of generalized tonic-clonic seizures by a wireless wrist accelerometer: A prospective, multicenter study”, Beniczky et al., Epilepsia, April 2013, pg. 58-61, discloses a wristband comprising a three-axis accelerometer and a wireless Bluetooth module. A generic seizure detection algorithm for detecting a GTCS is implemented in the device and the recorded data is transmitted to a control unit which then generates an alarm. This article does not teach or suggest that the implemented algorithm and the recorded acceleration data may be used to detect a PNES or other non-epileptic seizures. Furthermore, the article does not teach or suggest how a GTCS may be distinguished from a PNES.
U.S. Patent Application Publication 2012/0116183 A1 discloses a device for automatically distinguishing between an epileptic and non-epileptic seizure by measuring two signals on a body and comparing the signals with two index classes respectively in order to determine a first and second index value. The index values are used to determine whether the sensed seizure is an epileptic or non-epileptic seizure. Each seizure is automatically detected using a seizure detection algorithm, and a manual input from the patient or a caregiver is used to confirm whether the patient is having a seizure or not. This configuration provides a complex solution which requires a large amount of data processing as the classification process is performed each time a seizure is detected. The device is operated in an alarm mode informing the patient/caregiver of every detected seizure onset, thereby influencing the patient's assessment of when he/she is having a seizure.
International Patent Application Publication WO 2009/020880 A1 discloses a system for detecting epileptic seizures and PNES where the motor activity of the patient is continuously recorded using a sensor device and transferred to a computer unit that extracts features from the data stream using two dedicated analysis algorithms. Continuous video-EEG monitoring is used to determine when the seizures are occurring which are then used by the computer unit to define the time windows in which the data stream should be analyzed. The extracted features are then evaluated according to standard classification guidelines in order to determine whether the seizure is an epileptic seizure or a PNES. This solution requires the patient to be coupled to a conventional video-EEG monitoring system for logging seizures which in turn increases the cost for diagnosing a patient. The sensor device acts as a simple recording device, it is not able to detect when a seizure is occurring.